[£20,780 per annum. EPSRC CDT studentship covers stipend and likely tuition for 4 years.]

This fully funded PhD studentship at the University of Hull, in partnership with the EPSRC Centre for Doctoral Training (CDT) in Offshore Wind Energy Sustainability and Resilience, offers an exciting opportunity to develop explainable predictive AI models for assessing the environmental impact of offshore wind farms. The project is supervised by Dr Xinhui Ma and Dr Koorosh Aslansefat (University of Hull), and Prof Nina Dethlefs (Loughborough University), and is part of a collaboration between the Universities of Durham, Hull, Loughborough, and Sheffield.

Offshore wind energy is a cornerstone of the UK's net zero strategy, but its rapid expansion necessitates a deeper understanding of its environmental and socio-economic effects. This PhD will focus on creating transparent, explainable AI models to predict how offshore wind farms affect marine ecosystems, seabed mobility, and local industries such as fishing. The research will integrate diverse datasets from ecological monitoring, geospatial surveys, and socio-economic sources (including DEFRA and MMO datasets) to build models that capture both environmental and human dimensions of offshore wind development.

Unlike traditional 'black-box' AI, the models developed in this project will prioritize explainability, ensuring that predictions are accessible and trustworthy for regulators, developers, and local communities. By combining machine learning with physics-informed modeling, the project aims to deliver predictive tools that are both scientifically robust and interpretable to non-specialists. These tools will help stakeholders anticipate biodiversity changes, manage seabed risks, and understand socio-economic trade-offs associated with offshore wind projects.

The successful candidate will join a vibrant research environment at Hull and Loughborough, collaborating with other PhD students in the sustainable offshore wind cluster and engaging with industry partners and policymakers. The program includes an intensive six-month training period at the University of Hull, followed by ongoing professional development throughout the four-year scholarship. Students will gain expertise in AI, sustainability, and stakeholder engagement—skills highly valued in both academia and industry.

Funding: The studentship provides a stipend of £20,780 per annum, with tuition fees covered for four years.

Eligibility: Applicants should hold a First-class Honours degree, or a 2:1 Honours degree and a Masters, or a Distinction at Masters level with any undergraduate degree (or international equivalents) in Computer Science, Data Science, Mathematics and Statistics, or related quantitative disciplines. Strong programming and machine learning skills are essential. Experience or interest in environmental science and sustainability is highly desirable. Non-native English speakers or those requiring a Tier 4 visa must provide evidence of English proficiency (IELTS 7.0 overall, no less than 6.0 in each skill).

Application deadline: 5 January 2025. For more information and to apply, visit the project link or contact Dr Xinhui Ma at [email protected].